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플랫폼
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SOTA
객체 검출
Object Detection On Coco 2017
Object Detection On Coco 2017
평가 지표
mAP
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
mAP
Paper Title
UniRepLKNet-XL++
56.4
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
UniRepLKNet-L++
55.8
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
UniRepLKNet-B++
54.8
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
UniRepLKNet-S++
54.3
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
MixMIM-L
54.1
MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers
UniRepLKNet-S
53
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
MixMIM-B
52.2
MixMAE: Mixed and Masked Autoencoder for Efficient Pretraining of Hierarchical Vision Transformers
UniRepLKNet-T
51.7
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition
BiFormer-B (IN1k pretrain, MaskRCNN 12ep)
48.6
BiFormer: Vision Transformer with Bi-Level Routing Attention
DeBiFormer-B (IN1k pretrain, MaskRCNN 12ep)
48.5
DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention
BiFormer-S (IN1k pretrain, MaskRCNN 12ep)
47.8
BiFormer: Vision Transformer with Bi-Level Routing Attention
DeBiFormer-S (IN1k pretrain, MaskRCNN 12ep)
47.5
DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention
DeBiFormer-B (IN1k pretrain, Retina)
47.1
DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention
DeBiFormer-S (IN1k pretrain, Retina)
45.6
DeBiFormer: Vision Transformer with Deformable Agent Bi-level Routing Attention
YOLO-Drone
35.45
YOLO-Drone:Airborne real-time detection of dense small objects from high-altitude perspective
DyHead (SAP)
-
Stochastic Subsampling With Average Pooling
Lpixel
-
Paint Transformer: Feed Forward Neural Painting with Stroke Prediction
MaxViT-T
-
MaxViT: Multi-Axis Vision Transformer
DAT-T++
-
DAT++: Spatially Dynamic Vision Transformer with Deformable Attention
MaxViT-S
-
MaxViT: Multi-Axis Vision Transformer
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Object Detection On Coco 2017 | SOTA | HyperAI초신경